Cloud to Street - Microsoft Flood and Clouds Dataset

Stream data with DDA:

from dagshub.streaming import DagsHubFilesystem

fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/c2smsfloods-dataset")

fs.listdir("s3://radiant-mlhub/c2smsfloods")

Description:

This dataset consists of chips of Sentinel-1 and Sentinel-2 satellite data. Each Sentinel-1 chip contains a corresponding label for water and each Sentinel-2 chip contains a corresponding label for water and clouds. Data is stored in folders by a unique event identifier as the folder name. Within each event folder there are subfolders for Sentinel-1 (s1) and Sentinel-2 (s2) data. Each chip is contained in its own sub-folder with the folder name being the source image id, followed by a unique chip identifier consisting of a hyphenated set of 5 numbers. All bands of the satellite data, as well as the labels, and overview images are contained within the chip folder.

Contact:

This dataset consists of chips of Sentinel-1 and Sentinel-2 satellite data. Each Sentinel-1 chip contains a corresponding label for water and each Sentinel-2 chip contains a corresponding label for water and clouds. Data is stored in folders by a unique event identifier as the folder name. Within each event folder there are subfolders for Sentinel-1 (s1) and Sentinel-2 (s2) data. Each chip is contained in its own sub-folder with the folder name being the source image id, followed by a unique chip identifier consisting of a hyphenated set of 5 numbers. All bands of the satellite data, as well as the labels, and overview images are contained within the chip folder.

Update Frequency:

Not updated

Managed By:

https://radiant.earth/

Collabs:

• ASDI:
  • Tags: climate

Resources:

1. resource:
   • Description: Flood and Cloud Training Dataset
   • ARN: arn:aws:s3:::radiant-mlhub/c2smsfloods
   • Region: us-west-2
   • Type: S3 Bucket

Tags:

aws-pds, computer vision, deep learning, machine learning, floods, geospatial, earth observation, satellite imagery, cog, synthetic aperture radar